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Mitigating Popularity Bias for Users and Items with Fairness-centric Adaptive Recommendation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10115-011-0463-8openalex-snapshot
Data preprocessing techniques for classification without discrimination
inferredcites →https://doi.org/10.1080/00107510500052444openalex-snapshot
Power laws, Pareto distributions and Zipf's law
inferredcites →https://doi.org/10.1089/big.2016.0048openalex-snapshot
Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification
inferredcites →https://doi.org/10.1109/jas.2017.7510583openalex-snapshot
Generative adversarial networks: introduction and outlook
inferredcites →https://doi.org/10.1126/science.128.3317.195-bopenalex-snapshot
Puzzle-Math . George Gamow and Marvin Stern. Viking, New York, 1958. 119 pp. Illus. $2.50.
inferredcites →https://doi.org/10.1137/1.9781611972795.50openalex-snapshot
Measuring Discrimination in Socially-Sensitive Decision Records
inferredcites →https://doi.org/10.1145/1835804.1835895openalex-snapshot
Training and testing of recommender systems on data missing not at random
inferredcites →https://doi.org/10.1145/2043932.2043957openalex-snapshot
Item popularity and recommendation accuracy
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3109859.3109912openalex-snapshot
Controlling Popularity Bias in Learning-to-Rank Recommendation
inferredcites →https://doi.org/10.1145/3219819.3220088openalex-snapshot
Fairness of Exposure in Rankings
inferredcites →https://doi.org/10.1145/3278721.3278779openalex-snapshot
Mitigating Unwanted Biases with Adversarial Learning
inferredcites →https://doi.org/10.1145/3285029openalex-snapshot
Deep Learning Based Recommender System
inferredcites →https://doi.org/10.1145/3289600.3291027openalex-snapshot
Offline Evaluation to Make Decisions About PlaylistRecommendation Algorithms
inferredcites →https://doi.org/10.1145/3292500.3330745openalex-snapshot
Fairness in Recommendation Ranking through Pairwise Comparisons
inferredcites →https://doi.org/10.1145/3336191.3371783openalex-snapshot
Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback
inferredcites →https://doi.org/10.1145/3340531.3412152openalex-snapshot
Feedback Loop and Bias Amplification in Recommender Systems
inferredcites →https://doi.org/10.1145/3366423.3380196openalex-snapshot
FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms
inferredcites →https://doi.org/10.1145/3383313.3418487openalex-snapshot
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation
inferredcites →https://doi.org/10.1145/3397271.3401177openalex-snapshot
Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems
inferredcites →https://doi.org/10.1145/3404835.3462875openalex-snapshot
Causal Intervention for Leveraging Popularity Bias in Recommendation
inferredcites →https://doi.org/10.1145/3404835.3462919openalex-snapshot
AutoDebias: Learning to Debias for Recommendation
inferredcites →https://doi.org/10.1145/3404835.3462953openalex-snapshot
Policy-Gradient Training of Fair and Unbiased Ranking Functions
inferredcites →https://doi.org/10.1145/3442381.3449866openalex-snapshot
User-oriented Fairness in Recommendation
inferredcites →https://doi.org/10.1145/3442381.3450015openalex-snapshot
Learning Fair Representations for Recommendation: A Graph-based Perspective
inferredcites →https://doi.org/10.1145/3447548.3467289openalex-snapshot
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
inferredcites →https://doi.org/10.1145/3452740openalex-snapshot
Popularity Bias in False-positive Metrics for Recommender Systems Evaluation
inferredcites →https://doi.org/10.1145/3477495.3531763openalex-snapshot
Adversarial Graph Perturbations for Recommendations at Scale
inferredcites →https://doi.org/10.1145/3477495.3531890openalex-snapshot
Mitigating the Filter Bubble While Maintaining Relevance
inferredcites →https://doi.org/10.1145/3564284openalex-snapshot
Bias and Debias in Recommender System: A Survey and Future Directions
inferredcites →https://doi.org/10.1145/3594871openalex-snapshot
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-69978-8_3openalex-snapshot
Biases, Fairness, and Non-discrimination
inferred← citeshttps://doi.org/10.1007/978-3-031-69978-8_6openalex-snapshot
Conclusions and Open Challenges
inferred← citeshttps://doi.org/10.1007/s10844-023-00817-wopenalex-snapshot
EqBal-RS: Mitigating popularity bias in recommender systems
inferred← citeshttps://doi.org/10.1080/1448837x.2025.2605390openalex-snapshot
Smart recommendations in E-commerce using convolutional neural networks and collaborative filtering
inferred← citeshttps://doi.org/10.1093/comjnl/bxaf008openalex-snapshot
Improving recommendation fairness with dependency-based graph collaborative filtering
inferred← citeshttps://doi.org/10.1109/access.2025.3611026openalex-snapshot
Item Cold Start in E-Commerce Recommender Systems: A Survey
inferred← citeshttps://doi.org/10.1109/ccssta69471.2026.11635252openalex-snapshot
Inverse Inference and Adaptive Fairness Control in Hybrid Evaluation Systems
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10888260openalex-snapshot
BIGFR: Bridging Individual and Group Fairness in Recommendation Systems
inferred← citeshttps://doi.org/10.1109/icws67624.2025.00011openalex-snapshot
TDIC: Time-Aware Disentanglement of Interest and Conformity in Mobile App Recommendations
inferred← citeshttps://doi.org/10.1109/smc54092.2024.10831683openalex-snapshot
CSLP: Collaborative Solution to Long-Tail Problem and Popularity Bias in Sequential Recommendation
inferred← citeshttps://doi.org/10.1109/tai.2025.3575554openalex-snapshot
Causal Disentanglement for Tackling Popularity Bias in Sequential Recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2025.3638343openalex-snapshot
Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias
inferred← citeshttps://doi.org/10.1109/tkde.2026.3669816openalex-snapshot
Training-Free and Unbiased Graph Collaborative Filtering for Personalized Recommendations
inferred← citeshttps://doi.org/10.1145/3539618.3591947openalex-snapshot
Popularity Debiasing from Exposure to Interaction in Collaborative Filtering
inferred← citeshttps://doi.org/10.1145/3579995openalex-snapshot
Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1
inferred← citeshttps://doi.org/10.1145/3603163.3609041openalex-snapshot
Effects of the spiral of silence on minority groups in recommender systems
inferred← citeshttps://doi.org/10.1145/3610302openalex-snapshot
Fairness in Recommendation: Foundations, Methods, and Applications
inferred← citeshttps://doi.org/10.1145/3640457.3688027openalex-snapshot
Enhancing Cross-Domain Recommender Systems with LLMs: Evaluating Bias and Beyond-Accuracy Measures
inferred← citeshttps://doi.org/10.1145/3641276openalex-snapshot
Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines
inferred← citeshttps://doi.org/10.1145/3650042openalex-snapshot
Deconfounded Cross-modal Matching for Content-based Micro-video Background Music Recommendation
inferred← citeshttps://doi.org/10.1145/3687041openalex-snapshot
Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank
inferred← citeshttps://doi.org/10.1145/3705328.3748169openalex-snapshot
A Reproducibility Study of Product-side Fairness in Bundle Recommendation
inferred← citeshttps://doi.org/10.1145/3708982openalex-snapshot
Privacy-preserved and Responsible Recommenders: From Conventional Defense to Federated Learning and Blockchain
inferred← citeshttps://doi.org/10.1145/3720553.3746671openalex-snapshot
The Role of Fairness and Diversity in User Choices and Perceptions of Music Playlists
inferred← citeshttps://doi.org/10.1145/3744240openalex-snapshot
Causality-Inspired Fair Representation Learning for Multimodal Recommendation
inferred← citeshttps://doi.org/10.1145/3769296openalex-snapshot
A Hybrid Adaptive Sampling Strategy for Fair and Accurate Meta-learned User Modeling
inferred← citeshttps://doi.org/10.1145/3773078.3831741openalex-snapshot
PROMISE: Process Reward Models for Unlocking Test-Time Scaling Laws in Generative Recommendations
inferred← citeshttps://doi.org/10.1515/opis-2025-0043openalex-snapshot
A Dual-Adversarial Learning Framework with Explicit Constraints for Two-Sided Fairness in Recommendation System
inferred← citeshttps://doi.org/10.1609/aaai.v38i8.28689openalex-snapshot
Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems
inferred← citeshttps://doi.org/10.26599/tst.2024.9010212openalex-snapshot
Exploring and Mitigating the Impact of Popularity Bias for Dynamic API Composition Recommendations
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